The invention includes a noise suppression algorithm and a sharpening algorithm. The sharpening algorithm of the present invention is closely related to the noise suppression algorithm of the invention, since the success of these algorithms depends upon their ability to separate image detail from noise. Uniformly blurring the image (as in the prior art) achieves noise suppression, but unfortunately it also blurs image detail. Simple unsharp masking (as in the prior art) sharpens image detail but it also boosts noise. Hence, one goal of the invention is to distinguish image detail from noise while intelligently controlling the image components so as to perform both noise suppression and sharpening in the same image. The goal of the noise suppression algorithm of the invention is to suppress noise while leaving image detail untouched. The goal of the sharpening algorithm of the invention is to sharpen the image detail without boosting the noise.
In the present invention, the method used for noise suppression to discriminate image detail from noise is also employed to do the image sharpening, with appropriate modifications. A singular value decomposition (SVD) block transformation method has been shown in the related application referenced above to discriminate between image detail and noise, and is consequently used in the present invention to perform noise suppression. The same SVD noise suppression algorithm is employed in the invention with appropriate modifications to sharpen the image as well. For image sharpening, the invention does not need to work with the large block sizes disclosed in the related application. It is sufficient to use smaller block sizes (5.times.5 or 7.times.7 kernels).
Another embodiment of the invention includes the application of a non-linear gain function which will be described in detail later.